import argparse
from pathlib import Path

import requests
import torch
from PIL import Image

from transformers import (
    RobertaTokenizer,
    TrOCRConfig,
    TrOCRForCausalLM,
    TrOCRProcessor,
    VisionEncoderDecoderModel,
    ViTConfig,
    ViTImageProcessor,
    ViTModel,
)
from transformers.utils import logging


logging.set_verbosity_info()
__a    :	Union[str, Any]         =    logging.get_logger(__name__)





def 							UpperCAmelCase		(       lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				[]
				for i in range(encoder_config.num_hidden_layers				):
								# encoder layers: output projection, 2 feedforward neural networks and 2 layernorms
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.norm1.weight", F"encoder.encoder.layer.{i}.layernorm_before.weight")				)
								rename_keys.append((F"encoder.deit.blocks.{i}.norm1.bias", F"encoder.encoder.layer.{i}.layernorm_before.bias")				)
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.attn.proj.weight", F"encoder.encoder.layer.{i}.attention.output.dense.weight")				)
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.attn.proj.bias", F"encoder.encoder.layer.{i}.attention.output.dense.bias")				)
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.norm2.weight", F"encoder.encoder.layer.{i}.layernorm_after.weight")				)
								rename_keys.append((F"encoder.deit.blocks.{i}.norm2.bias", F"encoder.encoder.layer.{i}.layernorm_after.bias")				)
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.mlp.fc1.weight", F"encoder.encoder.layer.{i}.intermediate.dense.weight")				)
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.mlp.fc1.bias", F"encoder.encoder.layer.{i}.intermediate.dense.bias")				)
								rename_keys.append(
								    (F"encoder.deit.blocks.{i}.mlp.fc2.weight", F"encoder.encoder.layer.{i}.output.dense.weight")				)
								rename_keys.append((F"encoder.deit.blocks.{i}.mlp.fc2.bias", F"encoder.encoder.layer.{i}.output.dense.bias")				)

				# cls token, position embeddings and patch embeddings of encoder
				rename_keys.extend(
				    [
				        ('''encoder.deit.cls_token''', '''encoder.embeddings.cls_token'''),
				        ('''encoder.deit.pos_embed''', '''encoder.embeddings.position_embeddings'''),
				        ('''encoder.deit.patch_embed.proj.weight''', '''encoder.embeddings.patch_embeddings.projection.weight'''),
				        ('''encoder.deit.patch_embed.proj.bias''', '''encoder.embeddings.patch_embeddings.projection.bias'''),
				        ('''encoder.deit.norm.weight''', '''encoder.layernorm.weight'''),
				        ('''encoder.deit.norm.bias''', '''encoder.layernorm.bias'''),
				    ]				)

				return rename_keys





def 							UpperCAmelCase		(       lowercase				,     lowercase				):







				"""simple docstring"""



				for i in range(encoder_config.num_hidden_layers				):
								# queries, keys and values (only weights, no biases)
								__lowercase					     =				state_dict.pop(F"encoder.deit.blocks.{i}.attn.qkv.weight"				)

								__lowercase					     =				in_proj_weight[
								    : encoder_config.hidden_size, :
								]
								__lowercase					     =				in_proj_weight[
								    encoder_config.hidden_size : encoder_config.hidden_size * 2, :
								]
								__lowercase					     =				in_proj_weight[
								    -encoder_config.hidden_size :, :
								]





def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				dct.pop(lowercase				)
				__lowercase					     =				val





def 							UpperCAmelCase		(       lowercase				):







				"""simple docstring"""



				if "handwritten" in checkpoint_url:
								__lowercase					     =				'''https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg'''  # industry
								# url = "https://fki.tic.heia-fr.ch/static/img/a01-122-02-12.jpg" # have
								# url = "https://fki.tic.heia-fr.ch/static/img/a01-122-02-10.jpg" # let
								# url = "https://fki.tic.heia-fr.ch/static/img/a01-122-02.jpg"  #
								# url = "https://fki.tic.heia-fr.ch/static/img/a01-122.jpg"
				elif "printed" in checkpoint_url or "stage1" in checkpoint_url:
								__lowercase					     =				'''https://www.researchgate.net/profile/Dinh-Sang/publication/338099565/figure/fig8/AS:840413229350922@1577381536857/An-receipt-example-in-the-SROIE-2019-dataset_Q640.jpg'''
				__lowercase					     =				Image.open(requests.get(lowercase				,     stream=lowercase				).raw				).convert('''RGB'''				)
				return im





@torch.no_grad()
def 							UpperCAmelCase		(       lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				ViTConfig(image_size=384				,     qkv_bias=lowercase				)
				__lowercase					     =				TrOCRConfig()

				# size of the architecture
				if "base" in checkpoint_url:
								__lowercase					     =				768
				elif "large" in checkpoint_url:
								# use ViT-large encoder
								__lowercase					     =				1024
								__lowercase					     =				4096
								__lowercase					     =				24
								__lowercase					     =				16
								__lowercase					     =				1024
				else:
								raise ValueError('''Should either find \'base\' or \'large\' in checkpoint URL'''				)

				# the large-printed + stage1 checkpoints uses sinusoidal position embeddings, no layernorm afterwards
				if "large-printed" in checkpoint_url or "stage1" in checkpoint_url:
								__lowercase					     =				False
								__lowercase					     =				'''relu'''
								__lowercase					     =				1024
								__lowercase					     =				True
								__lowercase					     =				False
								__lowercase					     =				False

				# load HuggingFace model
				__lowercase					     =				ViTModel(lowercase				,     add_pooling_layer=lowercase				)
				__lowercase					     =				TrOCRForCausalLM(lowercase				)
				__lowercase					     =				VisionEncoderDecoderModel(encoder=lowercase				,     decoder=lowercase				)
				model.eval()

				# load state_dict of original model, rename some keys
				__lowercase					     =				torch.hub.load_state_dict_from_url(lowercase				,     map_location='''cpu'''				,     check_hash=lowercase				)['''model''']

				__lowercase					     =				create_rename_keys(lowercase				,     lowercase				)
				for src, dest in rename_keys:
								rename_key(lowercase				,     lowercase				,     lowercase				)
				read_in_q_k_v(lowercase				,     lowercase				)

				# remove parameters we don't need
				del state_dict["encoder.deit.head.weight"]
				del state_dict["encoder.deit.head.bias"]
				del state_dict["decoder.version"]

				# add prefix to decoder keys
				for key, val in state_dict.copy().items():
								__lowercase					     =				state_dict.pop(lowercase				)
								if key.startswith('''decoder'''				) and "output_projection" not in key:
												__lowercase					     =				val
								else:
												__lowercase					     =				val

    # load state dict
				model.load_state_dict(lowercase				)

				# Check outputs on an image
				__lowercase					     =				ViTImageProcessor(size=encoder_config.image_size				)
				__lowercase					     =				RobertaTokenizer.from_pretrained('''roberta-large'''				)
				__lowercase					     =				TrOCRProcessor(lowercase				,     lowercase				)

				__lowercase					     =				processor(images=prepare_img(lowercase				)				,     return_tensors='''pt'''				).pixel_values

				# verify logits
				__lowercase					     =				torch.tensor([[model.config.decoder.decoder_start_token_id]]				)
				__lowercase					     =				model(pixel_values=lowercase				,     decoder_input_ids=lowercase				)
				__lowercase					     =				outputs.logits

				__lowercase					     =				torch.Size([1, 1, 50265]				)
				if "trocr-base-handwritten" in checkpoint_url:
								__lowercase					     =				torch.tensor(
								    [-1.4502, -4.6683, -0.5347, -2.9291, 9.1435, -3.0571, 8.9764, 1.7560, 8.7358, -1.5311]				)
				elif "trocr-large-handwritten" in checkpoint_url:
								__lowercase					     =				torch.tensor(
								    [-2.6437, -1.3129, -2.2596, -5.3455, 6.3539, 1.7604, 5.4991, 1.4702, 5.6113, 2.0170]				)
				elif "trocr-base-printed" in checkpoint_url:
								__lowercase					     =				torch.tensor(
								    [-5.6816, -5.8388, 1.1398, -6.9034, 6.8505, -2.4393, 1.2284, -1.0232, -1.9661, -3.9210]				)
				elif "trocr-large-printed" in checkpoint_url:
								__lowercase					     =				torch.tensor(
								    [-6.0162, -7.0959, 4.4155, -5.1063, 7.0468, -3.1631, 2.6466, -0.3081, -0.8106, -1.7535]				)

				if "stage1" not in checkpoint_url:
								assert logits.shape == expected_shape, "Shape of logits not as expected"
								assert torch.allclose(logits[0, 0, :10]				,     lowercase				,     atol=1E-3				), "First elements of logits not as expected"

				Path(lowercase				).mkdir(exist_ok=lowercase				)
				print(F"Saving model to {pytorch_dump_folder_path}"				)
				model.save_pretrained(lowercase				)
				print(F"Saving processor to {pytorch_dump_folder_path}"				)
				processor.save_pretrained(lowercase				)


if __name__ == "__main__":
		__a    :	List[Any]         =    argparse.ArgumentParser()

		parser.add_argument(
		    """--checkpoint_url""",
		    default="""https://layoutlm.blob.core.windows.net/trocr/model_zoo/fairseq/trocr-base-handwritten.pt""",
		    type=str,
		    help="""URL to the original PyTorch checkpoint (.pth file).""",
		)
		parser.add_argument(
		    """--pytorch_dump_folder_path""", default=None, type=str, help="""Path to the folder to output PyTorch model."""
		)
		__a    :	Optional[int]         =    parser.parse_args()
		convert_tr_ocr_checkpoint(args.checkpoint_url, args.pytorch_dump_folder_path)
from typing import Any




class   _UpperCamelCase :


			"""simple docstring"""






			def __init__(  self ,  lowerCAmelCase__		)	->   int:

							'''simple docstring'''


							__lowercase					     =				data
							__lowercase					     =				None





			def __repr__(  self		)	->   str:

							'''simple docstring'''


							return F"Node({self.data})"




class   _UpperCamelCase :


			"""simple docstring"""






			def __init__(  self		)	->   Optional[Any]:

							'''simple docstring'''


							__lowercase					     =				None





			def __iter__(  self		)	->   Any:

							'''simple docstring'''


							__lowercase					     =				self.head
							while node:
											yield node.data
											__lowercase					     =				node.next





			def __len__(  self		)	->   int:

							'''simple docstring'''


							return sum(1 for _ in self		)





			def __repr__(  self		)	->   str:

							'''simple docstring'''


							return "->".join([str(lowerCAmelCase__		) for item in self]		)





			def __getitem__(  self ,  lowerCAmelCase__		)	->   Any:

							'''simple docstring'''


							if not 0 <= index < len(self		):
											raise ValueError('''list index out of range.'''		)
							for i, node in enumerate(self		):
											if i == index:
															return node
							return None





			def __setitem__(  self ,  lowerCAmelCase__ ,  lowerCAmelCase__		)	->   None:

							'''simple docstring'''


							if not 0 <= index < len(self		):
											raise ValueError('''list index out of range.'''		)
							__lowercase					     =				self.head
							for _ in range(lowerCAmelCase__		):
											__lowercase					     =				current.next
							__lowercase					     =				data





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__		)	->   None:

							'''simple docstring'''


							self.insert_nth(len(self		) ,  lowerCAmelCase__		)





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__		)	->   None:

							'''simple docstring'''


							self.insert_nth(0 ,  lowerCAmelCase__		)





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__ ,  lowerCAmelCase__		)	->   None:

							'''simple docstring'''


							if not 0 <= index <= len(self		):
											raise IndexError('''list index out of range'''		)
							__lowercase					     =				Node(lowerCAmelCase__		)
							if self.head is None:
											__lowercase					     =				new_node
							elif index == 0:
											__lowercase					     =				self.head  # link new_node to head
											__lowercase					     =				new_node
							else:
											__lowercase					     =				self.head
											for _ in range(index - 1		):
															__lowercase					     =				temp.next
											__lowercase					     =				temp.next
											__lowercase					     =				new_node





			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   None:  # print every node data

							'''simple docstring'''


							print(self		)





			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   Any:

							'''simple docstring'''


							return self.delete_nth(0		)





			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   Any:  # delete from tail

							'''simple docstring'''


							return self.delete_nth(len(self		) - 1		)





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__ = 0		)	->   Any:

							'''simple docstring'''


							if not 0 <= index <= len(self		) - 1:  # test if index is valid
											raise IndexError('''List index out of range.'''		)
							__lowercase					     =				self.head  # default first node
							if index == 0:
											__lowercase					     =				self.head.next
							else:
											__lowercase					     =				self.head
											for _ in range(index - 1		):
															__lowercase					     =				temp.next
											__lowercase					     =				temp.next
											__lowercase					     =				temp.next.next
							return delete_node.data





			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   bool:

							'''simple docstring'''


							return self.head is None





			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   None:

							'''simple docstring'''


							__lowercase					     =				None
							__lowercase					     =				self.head

							while current:
											# Store the current node's next node.
											__lowercase					     =				current.next
											# Make the current node's next point backwards
											__lowercase					     =				prev
											# Make the previous node be the current node
											__lowercase					     =				current
											# Make the current node the next node (to progress iteration)
											__lowercase					     =				next_node
							# Return prev in order to put the head at the end
							__lowercase					     =				prev





def 							UpperCAmelCase		(       ):







				"""simple docstring"""



				__lowercase					     =				LinkedList()
				assert linked_list.is_empty() is True
				assert str(lowercase				) == ""

				try:
								linked_list.delete_head()
								raise AssertionError  # This should not happen.
				except IndexError:
								assert True  # This should happen.

				try:
								linked_list.delete_tail()
								raise AssertionError  # This should not happen.
				except IndexError:
								assert True  # This should happen.

				for i in range(10				):
								assert len(lowercase				) == i
								linked_list.insert_nth(lowercase				,     i + 1				)
				assert str(lowercase				) == "->".join(str(lowercase				) for i in range(1				,     11				)				)

				linked_list.insert_head(0				)
				linked_list.insert_tail(11				)
				assert str(lowercase				) == "->".join(str(lowercase				) for i in range(0				,     12				)				)

				assert linked_list.delete_head() == 0
				assert linked_list.delete_nth(9				) == 10
				assert linked_list.delete_tail() == 11
				assert len(lowercase				) == 9
				assert str(lowercase				) == "->".join(str(lowercase				) for i in range(1				,     10				)				)

				assert all(linked_list[i] == i + 1 for i in range(0				,     9				)				) is True

				for i in range(0				,     9				):
								__lowercase					     =				-i
				assert all(linked_list[i] == -i for i in range(0				,     9				)				) is True

				linked_list.reverse()
				assert str(lowercase				) == "->".join(str(lowercase				) for i in range(-8				,     1				)				)





def 							UpperCAmelCase		(       ):







				"""simple docstring"""



				__lowercase					     =				[
				    -9,
				    100,
				    Node(77345112				),
				    '''dlrow olleH''',
				    7,
				    5555,
				    0,
				    -192.55555,
				    '''Hello, world!''',
				    77.9,
				    Node(10				),
				    None,
				    None,
				    12.20,
				]
				__lowercase					     =				LinkedList()

				for i in test_input:
								linked_list.insert_tail(lowercase				)

				# Check if it's empty or not
				assert linked_list.is_empty() is False
				assert (
				    str(lowercase				) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
				    "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
				)

				# Delete the head
				__lowercase					     =				linked_list.delete_head()
				assert result == -9
				assert (
				    str(lowercase				) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
				    "Hello, world!->77.9->Node(10)->None->None->12.2"
				)

				# Delete the tail
				__lowercase					     =				linked_list.delete_tail()
				assert result == 12.2
				assert (
				    str(lowercase				) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
				    "Hello, world!->77.9->Node(10)->None->None"
				)

				# Delete a node in specific location in linked list
				__lowercase					     =				linked_list.delete_nth(10				)
				assert result is None
				assert (
				    str(lowercase				) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
				    "Hello, world!->77.9->Node(10)->None"
				)

				# Add a Node instance to its head
				linked_list.insert_head(Node('''Hello again, world!'''				)				)
				assert (
				    str(lowercase				)
				    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
				    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
				)

				# Add None to its tail
				linked_list.insert_tail(lowercase				)
				assert (
				    str(lowercase				)
				    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
				    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
				)

				# Reverse the linked list
				linked_list.reverse()
				assert (
				    str(lowercase				)
				    == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
				    "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
				)





def 							UpperCAmelCase		(       ):







				"""simple docstring"""



				from doctest import testmod

				testmod()

				__lowercase					     =				LinkedList()
				linked_list.insert_head(input('''Inserting 1st at head '''				).strip()				)
				linked_list.insert_head(input('''Inserting 2nd at head '''				).strip()				)
				print('''\nPrint list:'''				)
				linked_list.print_list()
				linked_list.insert_tail(input('''\nInserting 1st at tail '''				).strip()				)
				linked_list.insert_tail(input('''Inserting 2nd at tail '''				).strip()				)
				print('''\nPrint list:'''				)
				linked_list.print_list()
				print('''\nDelete head'''				)
				linked_list.delete_head()
				print('''Delete tail'''				)
				linked_list.delete_tail()
				print('''\nPrint list:'''				)
				linked_list.print_list()
				print('''\nReverse linked list'''				)
				linked_list.reverse()
				print('''\nPrint list:'''				)
				linked_list.print_list()
				print('''\nString representation of linked list:'''				)
				print(lowercase				)
				print('''\nReading/changing Node data using indexing:'''				)
				print(F"Element at Position 1: {linked_list[1]}"				)
				__lowercase					     =				input('''Enter New Value: '''				).strip()
				print('''New list:'''				)
				print(lowercase				)
				print(F"length of linked_list is : {len(lowercase				)}"				)


if __name__ == "__main__":
		main()